• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.75-85
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• 2018

Objective : The purpose of this study aimed to find out about the impact of RAPAEL Smart Glove on cognitive function and Daily living. Method : While 15 experimental group was given 'RAPAEL Smart Glove', 15 control group was given traditional cognitive rehabilitation. LOTCA, NCSE and MBI were taken to assess cognitive function and activities of daily living of two group before and after each intervention. Result : Cognitive function and Activities of Daily Living of both experimental group and control group presented statistically significant difference before and after each intervention(p<.05). But Statistically, the experiment group presented a significant improvement. Conclusion : The result of this study indicates that the existing rehabilitation treatment and 'RAPAEL Smart Glove' together can produce good effect on cognitive function and activities of Daily Living of mild cognitive impairment patient.

• PNF and Movement
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• v.17 no.2
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• pp.199-206
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• 2019

Purpose: The purpose of this study was to evaluate the effects of a virtual upper extremity training program using the RAPAEL Smart Glove on upper extremity function in stroke survivors with chronic hemiparesis and to focus the training program development using the Smart Glove as a feasibility study. Methods: This study was conducted using a single group and pre-post test research design in the outpatient departments of local rehabilitation units. Ten chronic hemiparetic stroke survivors with a diagnosis of first stroke received therapeutic rehabilitation at the rehabilitation units. All the participants used a virtual reality program with the RAPAEL Smart Glove for 30 minutes per session 3 days a week over 8 weeks. They also received conventional occupational therapy with functional electrical stimulation for 40 minutes per session 3 days a week for 8 weeks as an additional therapy. To analyze the effects of this therapeutic intervention, four clinical measures, including the box-block test (BBT), the Wolf motor function test (WMFT), the trail-making score, the Jebsen Taylor hand function test (JTHFT), and grip strength, were used. Results: Upon completion of the intervention in week 8, all the participants demonstrated significant WMFT, JTT, BBT, grip strength, and trail-making score gains compared to the respective baselines at week 0. Conclusion: This study suggests that virtual upper extremity training using the RAPAEL Smart Glove has a reasonable and beneficial effects on upper extremity function in chronic hemiparetic stroke survivors.

• Journal of The Korean Society of Integrative Medicine
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• v.5 no.3
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• pp.1-9
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• 2017

Purpose: The purpose of this study was to investigate the effects of an immersive, virtual reality-based exercise program on range of motion and dexterity in the upper extremities of stroke patients. Methods: Fifteen patients with hemiparesis after stroke participated in this study. The participants participated in Rapael Semart GloveTM, an immersive, virtual reality-based exercise program, performed for 30 minutes-, 3 times per week for 4 weeks. The Rapael Smart GloveTM program and a Box and Block Test (BBT) were used to measure range of motion and to assess dexterity, respectively, pre-and post-intervention. Results: Range of motion in pronation and supination of the forearm and flexion, extension, and ulnar deviation of the wrist improved after the intervention. Dexterity measured by BBT also improved. However, range of motion in flexion and extension of the fingers and radial deviation of the wrist did not improve. Conclusion: This study presents the effects of an immersive, virtual reality-based exercise program on hand function. In the future, a study comparing an immersive, virtual reality- based exercise program to other upper-extremity interventions for stroke patients should be conducted. A study about the effects of an immersive virtual reality program on activities of daily living is also needed.

• Smart Media Journal
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• v.8 no.4
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• pp.53-57
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• 2019

In this paper, we propose a flex sensor-based data glove to track the movements of human fingers for virtual reality education. By putting flex sensors and utilizing an accelerometer, this data glove allows people to enjoy applications for virtual reality (VR) or augmented reality (AR). With the maximum and minimum values of the flex sensor at each finger joint, it determines an angle corresponding to the bending value of the flex sensor. It tracks the movements of fingers and hand gestures with respect to the angle values at finger joints. In order to prove the effectiveness of the proposed data glove, we implemented a VR classroom application.

• PNF and Movement
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• v.17 no.3
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• pp.369-378
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• 2019

Purpose: This study investigated the effects of virtual reality-based task training (VRBTT) using a smart glove on upper extremity function and activity of daily living in stroke patients. Methods: Twenty-nine patients with chronic stroke disease were randomly allocated to two groups: the VRBTT group (n=14) and the control group (n=15). All patients received 30 minutes of standard occupational therapy, 5 times a week, for 8 weeks. The VRBTT group performed an additional 30 minutes of virtual reality-based rehabilitation training, 5 times a week, for 8 weeks. Results: Both groups showed significant improvements in upper extremity function, yielding an increase in FMA and K-WMFT (p<0.05). There was a more significant increase in the VRBTT group before and after interventions (p<0.05). There was no significant difference in MAS for the control group (p>0.05); however, there was a significant increase for the VRBTT group (p<0.05). In the activities of daily living, there was a significant difference in the values for K-MBI (p<0.05). In addition, both groups showed a significant increase for K-MBI and K-RNLI (p<0.05). Conclusion: This study showed that VRBTT using smart gloves can have a more positive effect on upper extremity function and activities of daily living in stroke patients than conventional intervention methods. A variety of virtual reality-based contents and glove-shaped wearable devices will help stroke patients in rehabilitation clinics recover and return to society.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.147-154
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• 2016

Purpose: To evaluate statistical differences among three measurements of range of motion (ROM) with Rapael Smart Glove (RSG) group 1, 2 and manual goniometer group. To investigate reference value of the kinematic analysis for range of motion (ROM) of distal upper extremity with Rapael Smart Glove (RSG). Methods: Sixteen normal persons without limitation of motion (LOM) enrolled in the study. The study was performed at two separate times and by two investigators on 16 normal adults. We compared ROM with RSG for measuring joint angles. We compared degrees of forearm supination/pronation, wrist flexion/extension and radial deviation/ulnar deviation during ROM of 16 participants using RSG. After one week, degrees of each motion were measured in the same way by other investigator to evaluate the reliability. Results: Statistical differences among three groups were showed. Most results of paired t-test between two RSG groups were over 0.05 and exceptions are supination, extension, and finger %. Conclusion: Our findings demonstrate that ROM of normal persons obtained by kinematic analysis with RSG are not valid as normal reference value for distal upper extremity motion. But, the reliability of between two RSG groups was showed with paired t-test and Pearson's correlation except supination, extension and finger %.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.503-504
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• 2017

Recently, economic growth in the world has increased interest in healthy life, and the smart health care industry is growing. In the field of smart healthcare, wearable-type biometric information measurement technology has been highlighted due to the importance of IoT technology. The purpose of this study is to develop a wearable heart - rate monitoring system that can be applied to wearable health care and glove - type monitoring that enables convenient monitoring of heart rate during activity. For this purpose, a glove - type wearable health care system was developed and its performance was evaluated. Experimental results showed that the heartbeat monitoring was possible even in the presence of actual daily activities.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.686-695
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• 2020

The present study evaluated the manual dexterity and usability of conductive gloves when operating touchscreen devices in the cold. Twelve male subjects (23.3±1.5 years in age) participated in three experimental conditions: no gloves, fabric conductive and lambskin conductive gloves. Manual dexterity was tested using both Purdue Pegboard (PP) and ASTM dexterity tests at an air temperature of 5℃ and air humidity of 30%RH. Glove usability was tested through the following touchscreen tests: tap, double tap, long tab, drag, flick, and multi-touch. The results showed that manual dexterity according to the PP (2.5 mm of a pin diameter) and ASTM tests (8 mm of a stick diameter) was worse for the two glove conditions than for the no glove condition (p<.005). PP dexterity was better for the fabric glove condition than for the lambskin glove condition (p<.05); however, there was no difference in ASTM dexterity between the two glove conditions. Hand and finger skin temperatures were higher for the glove conditions than the bare hand condition (p<.05), with no differences between the two glove conditions. The touchscreen usability was the best for the no glove condition, followed by fabric gloves (p<.05). Wearing either fabric or lambskin gloves diminishes hand dexterity while maintaining hand and finger temperatures at higher levels. For improved hand dexterity in dealing with small numbers, letters on a touchscreen in cold environments, we recommend wearing fabric conductive gloves rather than lambskin conductive gloves.

• Safety and Health at Work
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• v.15 no.2
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• pp.129-138
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• 2024

The COVID-19 pandemic has led to a significant surge in glove usage, as recommended by the World Health Organization. Despite efforts to ensure the quality and safety of gloves, glove-associated skin diseases such as hand dermatitis have become ubiquitous, particularly among health care workers. This review discusses the prevalence, causes, and risk factors of hand dermatitis, as well as research efforts in medical gloves in the past decade to overcome glove-related hand dermatitis. Research papers from 2013 to 2022 were reviewed, selecting only 49 relevant papers from the Ovid, PubMed, and Scopus databases. The average prevalence of hand dermatitis among health care workers increased from 21.08% to 37.24% upon the impact of the COVID-19 pandemic. The cases are likely due to allergies to latex proteins, rubber additives, and accelerators commonly found in gloves. Using alternatives to latex gloves, such as accelerator-free and latex-free glove options, can help reduce allergy-induced hand dermatitis. Strict hand hygiene practices, such as frequent hand washing and the use of sanitizers, are also contributing factors in contracting hand dermatitis. Over the past decade, glove research advancements have focused mainly on reducing or immobilizing latex proteins. These include the use of biodegradable dialdehyde, sodium alginate, arctigenin, bromelain, papain, UV-LED, prototype photoreactors, and structure-modified nanosilica with silane A174. Two effective hand dermatitis preventive measures, i.e. an additional layer of glove liners and the use of gentle alcohol-based hand sanitizer, were recommended. These advancements represent promising steps towards mitigating hand dermatitis risks associated with glove usage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.890-896
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• 2022

In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.